Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi

Ezgi Demircan-Türeyen; Mustafa E. Kamaşak

doi:10.1109/TIPTEKNO.2015.7374561

Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi

Translated title of the contribution: An improved TvMin+DART algorithm to reconstruct multilabel images

Ezgi Demircan-Türeyen, Mustafa E. Kamaşak

Department of Computer Engineering

Istanbul Kultur University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

From the algebraic point of view, image reconstruction is an under-determined problem, due to the fact that the projection measurements are a lot fewer than the unknown pixels. Discrete algebraic reconstruction technique (DART) is an algorithm used to cope with this situation. DART solves a discrete linear inverse problem by combining an algebraic reconstruction procedure with a threshold segmentation. In order to improve accuracy, the TvMin+DART algorithm modified the subroutines of DART by exploiting total variation minimization technique (TvMin). However, this algorithm was developed for only binary images. In this paper, our TvMin+DART algorithm will be generalized to handle multilabel images as well, and an experimental research to compare the proposed method with the original DART and the conventional filtered backprojection (FBP) will be presented.

Translated title of the contribution	An improved TvMin+DART algorithm to reconstruct multilabel images
Original language	Turkish
Title of host publication	2015 Medical Technologies National Conference, TIPTEKNO 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467377652
DOIs	https://doi.org/10.1109/TIPTEKNO.2015.7374561
Publication status	Published - 6 Jan 2016
Event	Medical Technologies National Conference, TIPTEKNO 2015 - Bodrum, Turkey Duration: 15 Oct 2015 → 18 Oct 2015

Publication series

Name	2015 Medical Technologies National Conference, TIPTEKNO 2015

Conference

Conference	Medical Technologies National Conference, TIPTEKNO 2015
Country/Territory	Turkey
City	Bodrum
Period	15/10/15 → 18/10/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Access to Document

10.1109/TIPTEKNO.2015.7374561

Cite this

Demircan-Türeyen, E., & Kamaşak, M. E. (2016). Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi. In 2015 Medical Technologies National Conference, TIPTEKNO 2015 Article 7374561 (2015 Medical Technologies National Conference, TIPTEKNO 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TIPTEKNO.2015.7374561

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title = "{\c C}ok Etiketli Imgelerin Geri{\c c}atimi i{\c c}in Iyile{\c s}tirilmi{\c s} TvMin+DART Algoritmasi",

abstract = "From the algebraic point of view, image reconstruction is an under-determined problem, due to the fact that the projection measurements are a lot fewer than the unknown pixels. Discrete algebraic reconstruction technique (DART) is an algorithm used to cope with this situation. DART solves a discrete linear inverse problem by combining an algebraic reconstruction procedure with a threshold segmentation. In order to improve accuracy, the TvMin+DART algorithm modified the subroutines of DART by exploiting total variation minimization technique (TvMin). However, this algorithm was developed for only binary images. In this paper, our TvMin+DART algorithm will be generalized to handle multilabel images as well, and an experimental research to compare the proposed method with the original DART and the conventional filtered backprojection (FBP) will be presented.",

keywords = "algebraic reconstruction techniques, compressed sensing, discrete tomography, threshold segmentation, total variation minimization",

author = "Ezgi Demircan-T{\"u}reyen and Kama{\c s}ak, {Mustafa E.}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; Medical Technologies National Conference, TIPTEKNO 2015 ; Conference date: 15-10-2015 Through 18-10-2015",

year = "2016",

month = jan,

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doi = "10.1109/TIPTEKNO.2015.7374561",

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Demircan-Türeyen, E & Kamaşak, ME 2016, Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi. in 2015 Medical Technologies National Conference, TIPTEKNO 2015., 7374561, 2015 Medical Technologies National Conference, TIPTEKNO 2015, Institute of Electrical and Electronics Engineers Inc., Medical Technologies National Conference, TIPTEKNO 2015, Bodrum, Turkey, 15/10/15. https://doi.org/10.1109/TIPTEKNO.2015.7374561

Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi. / Demircan-Türeyen, Ezgi; Kamaşak, Mustafa E.
2015 Medical Technologies National Conference, TIPTEKNO 2015. Institute of Electrical and Electronics Engineers Inc., 2016. 7374561 (2015 Medical Technologies National Conference, TIPTEKNO 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi

AU - Demircan-Türeyen, Ezgi

AU - Kamaşak, Mustafa E.

PY - 2016/1/6

Y1 - 2016/1/6

N2 - From the algebraic point of view, image reconstruction is an under-determined problem, due to the fact that the projection measurements are a lot fewer than the unknown pixels. Discrete algebraic reconstruction technique (DART) is an algorithm used to cope with this situation. DART solves a discrete linear inverse problem by combining an algebraic reconstruction procedure with a threshold segmentation. In order to improve accuracy, the TvMin+DART algorithm modified the subroutines of DART by exploiting total variation minimization technique (TvMin). However, this algorithm was developed for only binary images. In this paper, our TvMin+DART algorithm will be generalized to handle multilabel images as well, and an experimental research to compare the proposed method with the original DART and the conventional filtered backprojection (FBP) will be presented.

AB - From the algebraic point of view, image reconstruction is an under-determined problem, due to the fact that the projection measurements are a lot fewer than the unknown pixels. Discrete algebraic reconstruction technique (DART) is an algorithm used to cope with this situation. DART solves a discrete linear inverse problem by combining an algebraic reconstruction procedure with a threshold segmentation. In order to improve accuracy, the TvMin+DART algorithm modified the subroutines of DART by exploiting total variation minimization technique (TvMin). However, this algorithm was developed for only binary images. In this paper, our TvMin+DART algorithm will be generalized to handle multilabel images as well, and an experimental research to compare the proposed method with the original DART and the conventional filtered backprojection (FBP) will be presented.

KW - algebraic reconstruction techniques

KW - compressed sensing

KW - discrete tomography

KW - threshold segmentation

KW - total variation minimization

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DO - 10.1109/TIPTEKNO.2015.7374561

M3 - Konferans katkısı

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T3 - 2015 Medical Technologies National Conference, TIPTEKNO 2015

BT - 2015 Medical Technologies National Conference, TIPTEKNO 2015

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - Medical Technologies National Conference, TIPTEKNO 2015

Y2 - 15 October 2015 through 18 October 2015

ER -

Çok Etiketli Imgelerin Geriçatimi için Iyileştirilmiş TvMin+DART Algoritmasi

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